Investigating internal waves east of the Hainan Island using optical satellite remote sensing data

Marginal water of east Hainan Island was an area that internal waves occurred frequently, however, few studies was found and mechanism for internal waves formation was unclear. In the paper, China Brazil earth Resources Satellite data (CBERS) was used to detect and calculate distribution, direction, wavelength and amplitude of internal waves in marginal water of east Hainan Island and the mechanism of internal waves formation was also analyzed, results showed that direction of internal wave was off shoreward and wavelength was about 150-200m . The mechanism for internal wave’s formation can be postulated as by upwelling or tide tracing back.     

罗布泊“大耳朵”地区多源遥感影像数据库的设计与实现

目前,由空间数据引擎管理遥感影像数据的技术已经非常成熟,但在对多源遥感影像数据的合理组织和有效管理以及数据共享方面,还需要寻求更有效的方法。本文在分析不同遥感影像类型的基础上,结合罗布泊“大耳朵”地区研究的需要,设计实现了该区多源遥感影像数据库。讨论了逻辑上设计相同空间分辨率和不同空间分辨率的多源遥感影像数据存储的方法。即根据遥感影像数据的空间分辨率进行分类,并通过遥感影像元数据表建立多源遥感影像数据之间的逻辑关联来组织和管理影像数据的设计方法。该方法的成功运用,为多源遥感影像数据库的设计与建设提供了参考。     

四川汶川“5.12”地震滑坡堰塞湖遥感监测分析

运用可见光、雷达和航片等不同空间分辨率的多源遥感数据,对四川汶川"5.12"地震灾区因地震诱发形成的大型堰塞湖进行了遥感监测,对堰塞湖发生的地点、数量以及空间分布规律进行了讨论。重点对唐家山堰塞湖进行了动态监测,提取了其堰塞湖回水长度、水面面积与水量等信息,并对这一结果进行了详细分析,为地震滑坡堰塞湖科学处置与减灾决策提供了科学依据。     

基于Global Mapper的地貌晕渲制图——以西安幅(Ⅰ-49)为例

地貌晕渲图自动制图是以计算机软、硬件为基础,对DEM数据实现的一种三维立体可视化表达。本文从地貌晕渲的基本理论出发,以我国1:100万标准分幅的西安幅(1-49)为例,采用Global Mapper软件实现了计算机地貌晕渲自动制作的全过程,主要内容包括:计算机地貌晕渲关键技术的实现,地貌晕渲效果与参数设置之间的关系,Global Mapper软件中各种参数设置的合理性分析,使用分层设色的办法对晕渲图进行色彩的设计,并利用PHOTOSHOP软件对结果进行整饰等。该方法可实现地貌晕渲图的自动制图。     

基于“DEM-NDVI-土地覆盖分类”的天山博格达自然遗产地山地垂直带提取与变化分析

本文基于Landsat影像数据获取天山博格达自然遗产地土地覆盖分类,结合归一化植被指数（NDVI）和数字高程模型（DEM）构建“DEM-NDVI-土地覆盖分类”散点图分析研究区植被受海拔和坡向的水热空间变化影响的分布特征,通过概率统计分析提取博格达遗产地山地垂直带,并结合研究区的气温、降水数据和NDVI变化特征分析垂直带变化的原因。研究结果表明：① 本文利用“DEM-NDVI-土地覆盖分类”散点图,揭示了研究区1989年和2016年的NDVI值和分类类别随着海拔上升的变化特征,其中NDVI值随着海拔上升呈现“倒U形”变化,而不同分类类别在一定的海拔区间内呈现出聚集效应,且不同分类类别有明显的高程界限。② 1989年和2016年博格达遗产地山地垂直带分带上限分别为：1278 m和1185 m（温带荒漠草原带）、1784 m和1759 m（山地草原带）、2706 m和2730 m（山地针叶林带）、3272 m和3293 m（高山草甸带）、3636 m和3690 m（高山垫状植被带）。③ 博格达遗产地1989年和2016年山地垂直带受区域气温升高和降雨增加的影响有较为明显的改变,其中温带荒漠草原带最为敏感,其上限变化最大,向下收缩93 m;山地针叶林带的分布范围则向两侧扩张49 m;山地草甸带带宽基本保持不变,但整体上移了约20 m;冰雪带则受到全球气候变暖的影响向上退缩54 m。     

A novel dynamic stretching solution to eliminate saturation effect in NDVI and its application in drought monitoring

The normalized difference vegetation index(NDVI) is one of the key input variables for developing drought indices.However,the NDVI quickly saturates in high vegetation surfaces,and thus,the generalization of a drought index over different ecosystems becomes a challenge.This paper presents a novel,dynamic stretching algorithm to overcome the saturation effect in NDVI.A scaling transformation function to eliminate saturation effects when the vegetation fraction(VF) is large is proposed.Dynamic range adjustment is conducted using three coefficients,namely,the normalization factor(a),the stretching range controlling factor(m),and the stretching size controlling factor(e).The results show that the stretched NDVI(S-NDVI) is more sensitive to vegetation fraction than NDVI when the VF is large,ranging from 0.75 to 1.00.Moreover,the saturation effect in NDVI is effectively removed by using the S-NDVI.Further analysis suggests that there is a good linear correlation between the S-NDVI and the leaf area index(LAI).At the same time,the proposed S-NDVI significantly reduces or even eliminates the saturation effect over high biomass.A comparative analysis is performed between drought indices derived from NDVI and S-NDVI,respectively.In the experiment,reflectance data from the moderate resolution imaging spectroradiometer(MODIS) products and in-situ observation data from the meteorological sites at a regional scale are used.In this study,the coefficient of determination(R2) of the stretched drought index(S-DI) is above 0.5,indicating the reliability of the proposed algorithm with surface soil moisture content.Thus,the S-DI is suggested to be used as a drought index in extended regions,thus regional heterogeneity should be taken into account when applying stretching method.     

青藏高原典型植被生长季遥感模型提取分析

物候变化是衡量全球气候变化最直接、敏感的指示器,针对青藏高原这个独特地域单元上特殊的高寒植被进行关键物候期遥感提取模型及植被物候时空变化的研究具有重要的意义。本文首先以反距离加权空间插值算法与Savitzky-Golay滤波算法相结合的数据重建模型获得高质量2003-2012年青藏高原MODIS归一化植被指数(NDVI)数据。在此数据基础上,分别利用动态阈值法、最大变化斜率法、logistic曲线拟合法3种遥感植被生长季提取模型,对青藏高原地区两种典型植被的生长季(SOS生长季开始期,EOS生长季结束期,LOS生长季长度)进行提取。通过对3种模型提取结果的对比分析,并结合日均温模型对提取结果的验证发现,动态阈值法为青藏高原地区典型植被生长季的最优遥感提取模型。该模型对近10 a的高分辨率典型高寒植被物候参量的反演及时空变化特征分析表明,受青藏高原水热及海拔梯度的影响,青藏高原植被物候变化呈现出从东南向西北的空间分异规律,随春季温度的升高,近10 a来青藏高原高寒草地总体呈现生长季开始期(SOS)提前(0.248 d/a)的趋势。     

Alternative Fuzzy Cluster segmentation of remote sensing images based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.     

基于超像元词包特征和主动学习的高分遥感影像变化检测

为解决高分辨率遥感影像变化检测中存在底层特征缺乏语义信息、像元级的检测结果存在“椒盐”现象以及监督分类中样本标注自动化程度较低,本文提出一种基于超像元词包特征和主动学习的变化检测方法。首先采用熵率分割算法获取叠加影像的超像元对象;其次提取两期影像像元点对间的邻近相关影像特征（相关度、斜率和截距）和顾及邻域的纹理变化强度特征（均值、方差、同质性和相异性）,经线性组合作为像元点对的底层特征;然后基于像元点对底层特征利用BOW模型构建超像元词包特征,并采用一种改进标注策略的主动学习方法从无标记样本池中优选信息量较大的样本,且自动标注样本类别;最后训练分类器模型完成变化检测。通过选用2组不同地区的GF-2影像和Worldview-Ⅱ影像作为数据源进行实验,实验结果中2组数据集的F1分数分别为0.8714、0.8554,正确率分别为0.9148、0.9022,漏检率分别为0.1681、0.1868,误检率分别为0.0852、0.0978。结果表明,该法能有效识别变化区域、提高变化检测精度。此外,传统主动学习方法与改进标注策略的主动学习方法的学习曲线对比显示,改进的标注策略可在较低精度损失下,有效提高样本标注自动化程度。